Unknown

Dataset Information

0

Circulating biomarkers and incident ischemic stroke in the Framingham Offspring Study.


ABSTRACT:

Objective

We related a panel of inflammatory biomarkers to risk of incident ischemic stroke (IIS) in a community-dwelling sample.

Methods

Stroke-free Framingham offspring attending examination cycle 7 (1998-2001) had 15 circulating inflammatory biomarkers measured. Cox proportional hazard models were used to calculate the hazard ratios (HRs) of IIS per SD increment of each biomarker. Model 1 included age and sex. Model 2 additionally adjusted for systolic blood pressure, hypertension treatment, current smoking, diabetes, cardiovascular disease, and atrial fibrillation. The continuous net reclassification improvement was used to assess the improvement in IIS risk prediction of statistically significant biomarkers from our main analysis over traditional stroke risk factors.

Results

In 3,224 participants (mean age 61 ± 9 years, 54% women), 98 experienced IIS (mean follow-up of 9.8 [±2.2] years). In model 1, ln-C-reactive protein (ln-CRP) (HR 1.28, 95% confidence interval [CI] 1.04-1.56), ln-tumor necrosis factor receptor 2 (ln-TNFR2) (HR 1.33, 95% CI 1.09-1.63), ln-total homocysteine (ln-tHcy) (HR 1.32, 95% CI 1.11-1.58), and vascular endothelial growth factor (VEGF) (HR 1.25, 95% CI 1.07-1.46) were associated with risk of IIS. All associations, except for ln-CRP, remained significant in model 2 (ln-TNFR2: HR 1.24, 95% CI 1.02-1.51; ln-tHcy: HR 1.20, 95% CI 1.01-1.43; and VEGF: HR 1.21, 95% CI 1.04-1.42). The addition of these 4 biomarkers to the clinical Framingham Stroke Risk Profile score improved stroke risk prediction (net reclassification improvement: 0.34, 0.12-0.57; p < 0.05).

Conclusions

Higher levels of 4 biomarkers-CRP, tHcy, TNFR2, and VEGF-increased risk of IIS and improved the predictive ability of the Framingham Stroke Risk Profile score. Further research is warranted to explore their role as potential therapeutic targets.

SUBMITTER: Shoamanesh A 

PROVIDER: S-EPMC5035987 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

2015-08-12 | E-GEOD-60319 | biostudies-arrayexpress
| S-EPMC3375331 | biostudies-literature
| S-EPMC2847685 | biostudies-literature
2015-08-12 | GSE60319 | GEO
| S-EPMC5005887 | biostudies-literature
| S-EPMC8423279 | biostudies-literature
| S-EPMC4219255 | biostudies-literature
| S-EPMC7763395 | biostudies-literature
| S-EPMC3250275 | biostudies-other
| S-EPMC8405795 | biostudies-literature